Konferenzbeitrag
Point and Density Forecasts for the Euro Area Using Many Predictors: Are Large BVARs Really Superior?
Forecast models with large cross-sections are often subject to overparameterization leading to unstable parameter estimates and hence inaccurate forecasts. Recent articles suggest that a large Bayesian vector autoregression (BVAR) with sufficient prior information dominates competing approaches. In this paper we evaluate the forecast performance of large BVAR in comparison to its most natural competitors, i.e. averaging of small-scale BVARs and factor augmented BVARs with and without shrinkage. We derive point and density forecasts for euro area real GDP growth and HICP inflation conditional on an information set which is appropriate for all approaches and find no consistent outperformance of the large BVAR. While it produces good point forecasts, the performance is poor when density forecasts are used to evaluate predictive ability. Moreover, the ranking of the different approaches depends inter alia on the target variable, the forecast horizon, the state of the business cycle, and on the size of the dataset. Overall, we find that a factor augmented BVAR with shrinkage is competitive in all setups.
- Sprache
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Englisch
- Erschienen in
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Series: Beiträge zur Jahrestagung des Vereins für Socialpolitik 2013: Wettbewerbspolitik und Regulierung in einer globalen Wirtschaftsordnung - Session: Forecasting ; No. E20-V3
- Klassifikation
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Wirtschaft
Bayesian Analysis: General
Model Evaluation, Validation, and Selection
Prices, Business Fluctuations, and Cycles: Forecasting and Simulation: Models and Applications
- Ereignis
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Geistige Schöpfung
- (wer)
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Berg, Tim Oliver
Henzel, Steffen
- Ereignis
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Veröffentlichung
- (wer)
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ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften, Leibniz-Informationszentrum Wirtschaft
- (wo)
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Kiel und Hamburg
- (wann)
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2013
- Handle
- Letzte Aktualisierung
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10.03.2025, 11:43 MEZ
Datenpartner
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Konferenzbeitrag
Beteiligte
- Berg, Tim Oliver
- Henzel, Steffen
- ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften, Leibniz-Informationszentrum Wirtschaft
Entstanden
- 2013